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        <center> <img src="http://rfly.buaa.edu.cn/images/research/VisualSensorNetworkFigure1.png" /> </center>
        <center> Figure 1 Structure of indoor multi-camera-based testbed </center>
        <p><span>Visual Sensor Network (VSN) is a sensor-based networks with spatially distributed smart cameras capable of processing image data locally and fusing images of a scene from different viewpoints. It has emerged as an important class of multi-camera distributed intelligent systems, with unique performance, complexity and quality of service challenges. Current optical motion capture systems are a successful example of how useful the multi-camera system can be. We have designed a comprehensive multi-camera-based testbed for 3D tracking and control of multiple unmanned aerial vehicles (UAVs). In the testbed, some reflective markers can be detected by smart cameras, and their positions are easily reconstructed by triangulation algorithms and Kalman filters. The proposed testbed is a comprehensive and complete platform with good scalability applicable for research on a variety of advanced guidance, navigation, and control algorithms.</span></p>
        <p><strong><span>Research Directions:</span></strong></p>
        <ul>
          <li><span>Design and implementation of a wireless visual sensor network for cooperative navigation and localization of UAVs.</span></li>
          <li><span>Accurate and flexible multi-camera calibration method of a visual sensor network.</span></li>
          <li><span>Optimal camera arrangement of a visual sensor network to obtain maximum coverage.</span></li>
          <li><span>Research on the calibration and localization problems caused by asynchronous cameras.</span></li>
          <li><span>Design and implementation of a simulation environment of a visual sensor network.</span></li>
        </ul>
        <center> <img src="http://rfly.buaa.edu.cn/images/research/VisualSensorNetworkFigure2.png" /> </center>
        <center> Figure 2 Indoor multi-camera-based testbed </center>
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